10 Computational EEG Analysis for Hyperscanning …
227
42. M. Nakanishi, Y. Wang, X. Chen et al., Enhancing detection of SSVEPs for a high-speed brain
speller using task-related component analysis. IEEE Trans. Biomed. Eng. 65(1), 104–112
(2018)
43. J. Pajula, J. Tohka, How many is enough? Effect of sample size in inter-subject correlation
analysis of fMRI. Comput. Intell. Neurosci. 2016, 2094601 (2016)
44. L. Parra, P. Sajda, Blind source separation via generalized eigenvalue decomposition. J. Mach.
Learn. Res. 4(Dec), 1261–1269 (2003)
45. A. Pérez, M. Carreiras, J.A. Duñabeitia, Brain-to-brain entrainment: EEG interbrain synchronization while speaking and listening. Sci. Rep. 7(1), 4190 (2017)
46. R. Raina, Y. Shen, A. Mccallum, A.Y. Ng, Classification with hybrid generative/discriminative
models, in Advances in neural information processing systems 16, Vancouver and Whistler,
British Columbia, Canada, 8–13 December 2003 (2004)
47. K. Sameshima, L.A. Baccalá, Using partial directed coherence to describe neuronal ensemble
interactions. J. Neurosci. Methods 94(1), 93–103 (1999)
48. P. Sauseng, W. Klimesch, What does phase information of oscillatory brain activity tell us
about cognitive processes? Neurosci. Biobehav. Rev. 32(5), 1001–1013 (2008)
49. L. Schilbach, B. Timmermans, V. Reddy et al., Toward a second-person neuroscience 1. Behav.
Brain Sci. 36(4), 393–414 (2013)
50. R.T. Schirrmeister, J.T. Springenberg, L.D.J. Fiederer et al., Deep learning with convolutional
neural networks for EEG decoding and visualization. Hum. Brain Mapp. 38(11), 5391–5420
(2017)
51. R. Schmälzle, F.E. Häcker, C.J. Honey, U. Hasson, Engaged listeners: shared neural processing
of powerful political speeches. Soc. Cogn. Affect. Neurosci. 10(8), 1137–1143 (2015)
52. C.E. Schroeder, P. Lakatos, Y. Kajikawa et al., Neuronal oscillations and visual amplification
of speech. Trends. Cogn. Sci. 12(3), 106–113 (2008)
53. N. Sciaraffa, G. Borghini, P. Aricò et al., Brain interaction during cooperation: evaluating local
properties of multiple-brain network. Brain Sci. 7(7), 90 (2017)
54. X. Shen, Q. Sun, Y. Yuan, A unified multiset canonical correlation analysis framework based
on graph embedding for multiple feature extraction. Neurocomputing 148, 397–408 (2015)
55. G. Shmueli, To explain or to predict? Stat. Sci. 25(3), 289–310 (2010)
56. M. Siegel, T.H. Donner, A.K. Engel, Spectral fingerprints of large-scale neuronal interactions.
Nat. Rev. Neurosci. 13(2), 121–134 (2012)
57. L.J. Silbert, C.J. Honey, E. Simony et al., Coupled neural systems underlie the production and
comprehension of naturalistic narrative speech. Proc. Natl. Acad. Sci. 111(43), E4687–E4696
(2014)
58. N. Sinha, T. Maszczyk, Z. Wanxuan et al., EEG hyperscanning study of inter-brain synchrony
during cooperative and competitive interaction, in 2016 IEEE International Conference on
Systems, Man, and Cybernetics (2016)
59. C.J. Stam, Nonlinear dynamical analysis of EEG and MEG: review of an emerging field. Clin.
Neurophysiol. 116(10), 2266–2301 (2005)
60. D.A. Stanley, R. Adolphs, Toward a neural basis for social behavior. Neuron 80(3), 816–826
(2013)
61. G.J. Stephens, L.J. Silbert, U. Hasson, Speaker–listener neural coupling underlies successful
communication. Proc. Natl. Acad. Sci. 107(32), 14425–14430 (2010)
62. C. Szymanski, A. Pesquita, A.A. Brennan et al., Teams on the same wavelength perform
better: Inter-brain phase synchronization constitutes a neural substrate for social facilitation.
NeuroImage 152, 425–436 (2017)
63. J. Toppi, G. Borghini, M. Petti et al., Investigating cooperative behavior in ecological settings:
an EEG hyperscanning study. PLoS One 11(4), e0154236 (2016)
64. D. Valeriani, R. Poli, C. Cinel, Enhancement of group perception via a collaborative brain—
computer interface. IEEE Trans. Biomed. Eng. 64(6), 1238–1248 (2017)
65. F. van Overwalle, Social cognition and the brain: a meta-analysis. Hum. Brain Mapp. 30(3),
829–858 (2009)
227
42. M. Nakanishi, Y. Wang, X. Chen et al., Enhancing detection of SSVEPs for a high-speed brain
speller using task-related component analysis. IEEE Trans. Biomed. Eng. 65(1), 104–112
(2018)
43. J. Pajula, J. Tohka, How many is enough? Effect of sample size in inter-subject correlation
analysis of fMRI. Comput. Intell. Neurosci. 2016, 2094601 (2016)
44. L. Parra, P. Sajda, Blind source separation via generalized eigenvalue decomposition. J. Mach.
Learn. Res. 4(Dec), 1261–1269 (2003)
45. A. Pérez, M. Carreiras, J.A. Duñabeitia, Brain-to-brain entrainment: EEG interbrain synchronization while speaking and listening. Sci. Rep. 7(1), 4190 (2017)
46. R. Raina, Y. Shen, A. Mccallum, A.Y. Ng, Classification with hybrid generative/discriminative
models, in Advances in neural information processing systems 16, Vancouver and Whistler,
British Columbia, Canada, 8–13 December 2003 (2004)
47. K. Sameshima, L.A. Baccalá, Using partial directed coherence to describe neuronal ensemble
interactions. J. Neurosci. Methods 94(1), 93–103 (1999)
48. P. Sauseng, W. Klimesch, What does phase information of oscillatory brain activity tell us
about cognitive processes? Neurosci. Biobehav. Rev. 32(5), 1001–1013 (2008)
49. L. Schilbach, B. Timmermans, V. Reddy et al., Toward a second-person neuroscience 1. Behav.
Brain Sci. 36(4), 393–414 (2013)
50. R.T. Schirrmeister, J.T. Springenberg, L.D.J. Fiederer et al., Deep learning with convolutional
neural networks for EEG decoding and visualization. Hum. Brain Mapp. 38(11), 5391–5420
(2017)
51. R. Schmälzle, F.E. Häcker, C.J. Honey, U. Hasson, Engaged listeners: shared neural processing
of powerful political speeches. Soc. Cogn. Affect. Neurosci. 10(8), 1137–1143 (2015)
52. C.E. Schroeder, P. Lakatos, Y. Kajikawa et al., Neuronal oscillations and visual amplification
of speech. Trends. Cogn. Sci. 12(3), 106–113 (2008)
53. N. Sciaraffa, G. Borghini, P. Aricò et al., Brain interaction during cooperation: evaluating local
properties of multiple-brain network. Brain Sci. 7(7), 90 (2017)
54. X. Shen, Q. Sun, Y. Yuan, A unified multiset canonical correlation analysis framework based
on graph embedding for multiple feature extraction. Neurocomputing 148, 397–408 (2015)
55. G. Shmueli, To explain or to predict? Stat. Sci. 25(3), 289–310 (2010)
56. M. Siegel, T.H. Donner, A.K. Engel, Spectral fingerprints of large-scale neuronal interactions.
Nat. Rev. Neurosci. 13(2), 121–134 (2012)
57. L.J. Silbert, C.J. Honey, E. Simony et al., Coupled neural systems underlie the production and
comprehension of naturalistic narrative speech. Proc. Natl. Acad. Sci. 111(43), E4687–E4696
(2014)
58. N. Sinha, T. Maszczyk, Z. Wanxuan et al., EEG hyperscanning study of inter-brain synchrony
during cooperative and competitive interaction, in 2016 IEEE International Conference on
Systems, Man, and Cybernetics (2016)
59. C.J. Stam, Nonlinear dynamical analysis of EEG and MEG: review of an emerging field. Clin.
Neurophysiol. 116(10), 2266–2301 (2005)
60. D.A. Stanley, R. Adolphs, Toward a neural basis for social behavior. Neuron 80(3), 816–826
(2013)
61. G.J. Stephens, L.J. Silbert, U. Hasson, Speaker–listener neural coupling underlies successful
communication. Proc. Natl. Acad. Sci. 107(32), 14425–14430 (2010)
62. C. Szymanski, A. Pesquita, A.A. Brennan et al., Teams on the same wavelength perform
better: Inter-brain phase synchronization constitutes a neural substrate for social facilitation.
NeuroImage 152, 425–436 (2017)
63. J. Toppi, G. Borghini, M. Petti et al., Investigating cooperative behavior in ecological settings:
an EEG hyperscanning study. PLoS One 11(4), e0154236 (2016)
64. D. Valeriani, R. Poli, C. Cinel, Enhancement of group perception via a collaborative brain—
computer interface. IEEE Trans. Biomed. Eng. 64(6), 1238–1248 (2017)
65. F. van Overwalle, Social cognition and the brain: a meta-analysis. Hum. Brain Mapp. 30(3),
829–858 (2009)